Analytics & Monitoring Claude 스킬
analytics & monitoring Claude 스킬을 발견하세요. 47개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Metabase Frontend Analytics Events
Standardizes the implementation of product analytics events within the Metabase frontend using TypeScript schemas and Snowplow tracking.
PostHog Agent Mode Architect
Guides developers through the end-to-end process of creating and configuring specialized context-aware modes for the PostHog AI assistant.
Python Observability Patterns
Implements production-grade observability in Python applications through structured logging, Prometheus metrics, and distributed tracing.
Startup Metrics Framework
Provides a comprehensive framework for calculating, tracking, and optimizing key performance indicators for SaaS, marketplace, and consumer startup business models.
Distributed Tracing & Observability
Implements end-to-end request tracking across microservices using Jaeger, Tempo, and OpenTelemetry to identify performance bottlenecks and debug complex system failures.
Service Mesh Observability
Implements comprehensive monitoring, distributed tracing, and performance visualization for Istio, Linkerd, and OpenTelemetry architectures.
SLO Implementation Framework
Defines and implements Service Level Indicators (SLIs) and Service Level Objectives (SLOs) to establish measurable reliability targets.
KPI Dashboard Design
Designs data-driven KPI dashboards with optimized metric selection, visualization best practices, and real-time monitoring patterns.
Prometheus Configuration
Configures comprehensive metric collection, alerting, and monitoring infrastructure using Prometheus.
Incident Runbook Templates
Generates production-ready incident response runbooks and structured procedures for service outages and database failures.
Python Performance Optimizer
Profiles and optimizes Python code to eliminate execution bottlenecks and reduce memory consumption.
Grafana Dashboard Architect
Designs and manages production-grade Grafana dashboards for real-time system observability and metric visualization.
KPI Dashboard Design
Designs high-impact KPI dashboards using strategic metric selection, industry-standard visualization patterns, and data monitoring best practices.
Distributed Tracing
Implements and configures distributed tracing systems using Jaeger and Tempo to monitor request flows and identify performance bottlenecks across microservice architectures.
SLO Implementation
Defines and implements Service Level Indicators (SLIs) and Service Level Objectives (SLOs) to establish measurable reliability targets and manage error budgets.
Service Mesh Observability
Implements comprehensive observability patterns for service meshes including distributed tracing, metrics, and dependency visualization.
Prometheus Configuration
Configures Prometheus for comprehensive metric collection, alerting, and observability across infrastructure and applications.
dbt Transformation Patterns
Implements production-ready analytics engineering patterns using dbt for scalable, documented, and tested data transformation pipelines.
Data Storytelling
Transforms raw data into compelling, actionable narratives through structured story frameworks and effective visualization techniques.
Risk Metrics Calculation
Calculates comprehensive portfolio risk indicators, including Value at Risk (VaR), expected shortfall, and risk-adjusted return ratios.
Grafana Dashboards
Designs and implements production-ready Grafana dashboards for real-time system observability and application performance monitoring.
Python Performance Optimization
Profiles, analyzes, and accelerates Python code through CPU/memory diagnostics, efficient data structures, and advanced parallelization techniques.
LangSmith Fetch
Debugs LangChain and LangGraph agents by fetching and analyzing execution traces directly from LangSmith Studio.
Google Analytics Analysis
Analyzes Google Analytics data to provide actionable website performance insights and data-driven optimization recommendations.
V3 Performance Optimization
Optimizes Claude-flow agent performance through Flash Attention, HNSW indexing, and aggressive memory management.
Performance Analysis
Identifies performance bottlenecks and generates actionable optimization recommendations for intelligent multi-agent swarms.
Runtime Evidence Debugger
Automates runtime log collection and hypothesis testing to fix complex bugs using empirical evidence instead of guesswork.
Bloblang Authoring
Generates, tests, and debugs Bloblang transformation scripts for Redpanda Connect data pipelines.
Claude-Mem Troubleshooter
Diagnoses and repairs installation, worker, and database issues for the Claude-Mem persistent memory plugin.
Phoenix AI Observability CLI
Debugs and optimizes LLM applications by analyzing traces, experiments, and evaluation datasets through the Phoenix CLI.
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